Mobile Devices and New Opportunities for E-Commerce

As far as the exploration in the presented master thesis showed, there is very few information around the Internet about how to deal with the mobile application on the specific niche for the internet business. The problem was revealed after deep literature analysis based on newly created scientific articles in the sphere of internet sales, stores and their mobile adaptivity issues. It is needed to know whether the application should be created or not, how much business should spend on it and which functionality it should consists of. In a scope of the work, specific methodology for data collection has been introduced. The data should form the balanced dataset with different internet stores based on its size. Some part of information, which is about customers’ user experience is collected using crowdsourcing platform. As a result, the mathematical model has been created, based on machine learning algorithms. The model has been used for recommendations’ service implementation. Service takes the basic information from the business (such as domain name and some parameters such as existence of mobile applications), produces values for the factors, that play role in the model, and generates the recommendation for what should be done to satisfy the requirements on its niche.